Research On Techniques Of Wireless Localization And Location Verification Service

In recent years,the rapid increase of location-based service and demand have greatly promoted the development of localization technology and location verification service technology,and has also made the in-depth research of localization technology and location verification service technology more urgent.The wireless localization based on Wi Fi has become an important research topic due to its convenience and low cost.How to use the impact of the moving object on the received signal to achieve object's localization is very meaningful and promising.Compared to received signal strength,channel state information from the physical layer can provide rich and fine-grained localization information.Therefore,the fingerprint-based localization algorithm is explored with the channel state information.The key to the normal operation of location-based service is whether the correct location information can be obtained.However,in some cases,it is necessary to send a request to the user to obtain the user's location information.Mean while,if an illegal user provides wrong location information for location spoofing,it will seriously affect the user's safety.In recent years,how to effectively prevent location spoofing has been a topic favored by scientific researchers,and location verification service technology is an effective method to prevent location spoofing.Therefore,this paper also focus on the location verification technology.The specific research contents of wireless localization technology and location verification service technology are as follows:1.An indoor localization method based on CSI-MIMO(Channel State Information-Multiple Input Multiple Output)is proposed.Firstly,the localization fingerprint is constructed.It can reflect the time-frequency and space-frequency characteristics by an AP.Then,an algorithm to reduce the dimensionality of localization fingerprint is proposed to reduce the redundant information in fingerprint.Finally,the log-normal distribution model is used to calculate the conditional probability in the Bayesian classifier to predict the location of the moving object.The experimental results show that,compared to other CSI-based localization methods,the indoor localization method based on CSI-MIMO proposed in this paper can improve the localization accuracy more effectively.2.An indoor localization method based on CSI-MIMO image is proposed.In order to deal with the abnormal amplitude in the CSI measurements,an abnormal amplitude processing algorithm is proposed.This algorithm can adaptively calculate the cut-off distance,which makes up for the shortage of manually setting the cut-off distance,so as to better deal with the outliers in the data.In order to provide more localization features,an image fingerprint structure model based on CSI-MIMO is established.In order to improve the localization accuracy,a deep learning network with loss function of cross entropy plus L_{1 2,}mixed norm is designed.The experimental results show that the localization accuracy of the proposed indoor localization method based on CSI-MIMO image can reach 97%.3.An improved location verification service technology is proposed.Firstly,according to the log-normal propagation model,the composite log-normal shadowing model is designed.Then,according to the sequential detection method,the decision rules of location verification service model are formulated.Finally,according to the location verification service model and decision rules,the false alarm rate and detection rate of the location verification service model are obtained.The experimental results verify the effectiveness of this method in user's location verification.